Exploring structural variability in X-ray crystallographic models using protein local optimization by torsion-angle sampling.

ABSTRACT: Modeling structural variability is critical for understanding protein function and for modeling reliable targets for in silico docking experiments. Because of the time-intensive nature of manual X-ray crystallographic refinement, automated refinement methods that thoroughly explore conformational space are essential for the systematic construction of structurally variable models. Using five proteins spanning resolutions of 1.0-2.8 A, it is demonstrated how torsion-angle sampling of backbone and side-chain libraries with filtering against both the chemical energy, using a modern effective potential, and the electron density, coupled with minimization of a reciprocal-space X-ray target function, can generate multiple structurally variable models which fit the X-ray data well. Torsion-angle s

SUBMITTER: Knight JL 

PROVIDER: S-EPMC2631124 | biostudies-literature | 2008 Apr

REPOSITORIES: biostudies-literature